Brokerage Operations Data Analyst

• Analyze current operational processes to identify inefficiencies and recommend improvements.
• Develop and implement data-driven strategies to streamline operations and reduce costs.

Risk Reduction:

• Conduct risk assessments and identify potential areas of operational risk.
• Develop and implement risk mitigation strategies using data analysis and predictive modeling.

Growth Opportunity Identification:

• Analyze market trends, client behaviors, and trading patterns to identify growth opportunities.
• Provide insights and recommendations to the President and senior management to support strategic decision-making.

Data Management and Reporting:

• Collect, organize, and analyze large datasets to provide actionable insights.
• Create and maintain dashboards and reports to track key performance indicators (KPIs) and other critical metrics.

Ad Hoc Projects:

• Support various ad hoc projects as requested by the President or senior management.
• Provide data analysis and insights to support project goals and objectives.

Collaboration and Communication:

• Work closely with different departments, including trading, compliance, IT, and client services, to gather necessary data and insights.
• Present findings and recommendations to the President and other senior leaders clearly and concisely.

• Bachelor s degree in Finance, Business, Data Science, Statistics, or a related field.
• Advanced degrees or relevant certifications (e.g., CFA, FRM, Data Science certifications) preferred.
• Minimum of 2-3 years of experience in data analysis, preferably within the financial services or brokerage industry.
• Proven track record of conducting complex data analyses to drive operational improvements and strategic decisions.
• Proficiency in data analysis tools and software such as SQL, Python, R, Excel, and data visualization tools
• Strong understanding of financial markets, trading operations, and brokerage services.
• Strong communication and presentation skills, with the ability to convey complex data insights to non-technical stakeholders.
• Ability to work independently, manage priorities, and meet deadlines in a fast-paced environment.
• High ethical standards and a commitment to maintaining confidentiality